Web inspection systems utilize today imaging techniques for detecting defects and other anomalies. Holes, spots and dirt particles are examples of defects and wrinkles, streaks and slime spots are examples of weak defects to be detected for paper makers. Correspondingly, for sheet-metal makers, slag inclusions, cracks and scratches are examples of defects and weak cracks, weak scratches and indentations are examples of weak defects to be detected. In these cases, the weak defect causes only a slight change to the intensity level of the digital video signal compared to the mean variation of the signal measured from a faultless product.
Currently weak, elongated defects on a web are best detected by averaging or integrating methods. The optimal result is found only when the defect runs exactly in the cross direction of the web, the defect runs exactly in the machine direction of the web, or the defect runs in some exact angle direction of the web product.
Matching filters or two-dimensional Finite Impulse Response (FIR) filters (for example edge operators) are utilized for the detection of weak defects, but the amount of defect sizes and shapes is limited. For instance in US 2002054293 A1 is described how to find optimal matching filters for textured materials.
The traditional way to detect streaks is to integrate or average the video signal in machine direction in order to improve the Signal-to-Noise (S/N) ratio. For increased cross-directional resolutions of digital cameras and high demands for detecting weaker streaks, the traditional method is not adequate. As high cross-directional resolutions are used, the number of cross-directional pixel positions is high and the width of one pixel is small. This may lead to problems in the traditional method for example due to normal oscillations of the machinery, since the web and thus also the streak may oscillate and a narrow streak may move away from its original cross-directional pixel position. Thus, simple averaging or integration in the machine direction is not optimal for streak detection. The streak detection method should be capable of following the streak whenever the cross-directional position changes slightly.
There is a need for a detection method capable of handling defects including weak defects.